# MIPLIB 2010

@article{Koch2011MIPLIB2, title={MIPLIB 2010}, author={Thorsten Koch and Tobias Achterberg and Erling Andersen and Oliver Bastert and Timo Berthold and Robert E. Bixby and Emilie Danna and Gerald Gamrath and Ambros M. Gleixner and Stefan Heinz and Andrea Lodi and Hans D. Mittelmann and Ted K. Ralphs and Domenico Salvagnin and Daniel E. Steffy and Kati Wolter}, journal={Mathematical Programming Computation}, year={2011}, volume={3}, pages={103-163} }

This paper reports on the fifth version of the Mixed Integer Programming Library. [] Key Method For the first time, we include scripts to run automated tests in a predefined way. Further, there is a solution checker to test the accuracy of provided solutions using exact arithmetic.

## 288 Citations

### Solving Hard MIPLIB2003 Problems with ParaSCIP on Supercomputers: An Update

- Computer Science2014 IEEE International Parallel & Distributed Processing Symposium Workshops
- 2014

For the first time, computational results of single runs for two open MIPLIB2003 instances could be solved by ParaSCIP in more than ten consecutive runs, restarting from checkpointing files are presented.

### Progress in presolving for mixed integer programming

- BusinessMath. Program. Comput.
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Three presolving techniques for solving mixed integer programming problems (MIPs) that were implemented in the academic MIP solver SCIP are described and the computational results show that the combination of all three presolved techniques almost halves the solving time for the considered supply chain management problems.

### Verifying Integer Programming Results

- Computer ScienceIPCO
- 2017

This paper proposes a certificate format designed with simplicity in mind, which is composed of a list of statements that can be sequentially verified using a limited number of inference rules, and extends the exact rational version of the MIP solver SCIP to produce such certificates.

### The Ubiquity Generator Framework: 7 Years of Progress in Parallelizing Branch-and-Bound

- Computer ScienceOR
- 2017

ParaSCIP is the most successful parallel MILP solver in terms of solving previously unsolvable instances from the well-known benchmark instance set MIPLIB by using supercomputers.

### Reconsidering Mixed Integer Programming and MIP-Based Hybrids for Scheduling

- Business, Computer ScienceCPAIOR
- 2012

It is concluded that both MIP and CIP are technologies that should be considered along with CP for solving scheduling problems and two tightly coupled hybrid models based on constraint integer programming are formulated.

### QPLIB: a library of quadratic programming instances

- Computer ScienceMath. Program. Comput.
- 2019

This paper proposes a simple taxonomy for QP instances leading to a systematic problem selection mechanism, and briefly survey the field of QP, giving an overview of theory, methods and solvers.

### Solving Open MIP Instances with ParaSCIP on Supercomputers Using up to 80,000 Cores

- Computer Science2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
- 2016

The basic parallelization mechanism of ParaSCIP is described, improvements of the dynamic load balancing and novel techniques to exploit the power of parallelization for MIP solving are described.

### The SCIP Optimization Suite 5.0

- Computer Science
- 2017

New features and enhanced algorithms made available in version 5.0 of the SCIP Optimization Suite, in particular for the LP solver SoPlex, the Steiner tree solver SCIP-Jack, the MISDP solverSCIP-SDP, and the parallelization framework UG are described.

### MIPLIB 2017: data-driven compilation of the 6th mixed-integer programming library

- Computer ScienceMath. Program. Comput.
- 2021

For the first time, these sets were compiled using a data-driven selection process supported by the solution of a sequence of mixed integer optimization problems, which encode requirements on diversity and balancedness with respect to instance features and performance data.

### Benchmarks for Current Linear and Mixed Integer Optimization Solvers

- Computer Science
- 2015

Computational performance of current optimization packages for solving large scale LP and MILP optimization problems is discussed and attractiveness for academic research is given.

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